메뉴 건너뛰기




Volumn 4, Issue 1, 2000, Pages 57-65

The Application of Hybrid Evolving Connectionist Systems to Image Classification

Author keywords

Evolving fuzzy neural networks; Hybrid systems; Image classification; Neural fuzzy systems

Indexed keywords

CASE BASED REASONING; FUZZY INFERENCE; FUZZY NEURAL NETWORKS; FUZZY SYSTEMS; GRADING; HYBRID SYSTEMS; NETWORK LAYERS; REMOTE SENSING; SUPERVISED LEARNING;

EID: 0009986284     PISSN: 13430130     EISSN: 18838014     Source Type: Journal    
DOI: 10.20965/jaciii.2000.p0057     Document Type: Article
Times cited : (3)

References (41)
  • 4
    • 0027875503 scopus 로고
    • Hybrid neural nets can be fuzzy controllers and fuzzy expert systems
    • J J. Buckley and Y. Hayashi, "Hybrid neural nets can be fuzzy controllers and fuzzy expert systems, " Fuzzy Sets and Systems, 60, 135-142, (1993).
    • (1993) Fuzzy Sets and Systems , vol.60 , pp. 135-142
    • Buckley, J J.1    Hayashi, Y.2
  • 6
    • 0020968740 scopus 로고
    • Assessing Landsat Classification Accuracy using Discrete Multivariate Analysis Statistical Techniques
    • R.G. Congalton, R.G. Oderwald and R.A. Mead, "Assessing Landsat Classification Accuracy using Discrete Multivariate Analysis Statistical Techniques, " Photogrammetric Engineering and Remote Sensing, 49-12, 1671)678, (1983).
    • (1983) Photogrammetric Engineering and Remote Sensing , vol.49-12 , Issue.1671 , pp. 678
    • Congalton, R.G.1    Oderwald, R.G.2    Mead, R.A.3
  • 7
    • 0032762906 scopus 로고    scopus 로고
    • An Evolutionary Algorithm for the registration of 3-D Surface Representations
    • D. Fischer, P. Kohlhcpp and F, Bulling, " An Evolutionary Algorithm for the registration of 3-D Surface Representations, " Pattern Recognition, 32-1, 53-96, (1999).
    • (1999) Pattern Recognition , vol.32-1 , pp. 53-96
    • Fischer, D.1    Kohlhcpp, P.2    Bulling, F3
  • 8
    • 0032505168 scopus 로고    scopus 로고
    • Sharpening Fuzzy Classification Output to Refine the Representation of Sub-Pixel Land Cover Distribution
    • G.M. Foody, "Sharpening Fuzzy Classification Output to Refine the Representation of Sub-Pixel Land Cover Distribution, " International Journal of Remote Sensing, 19-13, 2593-2599, (1998).
    • (1998) International Journal of Remote Sensing , vol.19-13 , pp. 2593-2599
    • Foody, G.M.1
  • 10
    • 0028268852 scopus 로고
    • On the Principles of Fuzzy Neural Networks
    • M.M. Gupta and D.H. Rao, "On the Principles of Fuzzy Neural Networks, " Fuzzy Sets and Systems, 61-1, 1-18, (1994).
    • (1994) Fuzzy Sets and Systems , vol.61-1 , pp. 1-18
    • Gupta, M.M.1    Rao, D.H.2
  • 11
    • 0347075125 scopus 로고    scopus 로고
    • Statistical, Connectionist, and Fuzzy Inference Techniques for Image Classification
    • S.A. Israel and N.K. Kasabov, "Statistical, Connectionist, and Fuzzy Inference Techniques for Image Classification, " SPIE Journal of Electronic Imaging, 6-3, 337-347, (1997).
    • (1997) SPIE Journal of Electronic Imaging , vol.6-3 , pp. 337-347
    • Israel, S.A.1    Kasabov, N.K.2
  • 12
    • 0027601884 scopus 로고
    • ANFIS: Adaptive Network-Based Fuzzy Inference System
    • May-June (1993)
    • R. Jang, "ANFIS: Adaptive Network-Based Fuzzy Inference System, " IEEE Trans, on Syst., Man, Cybernetics, 23-3, May-June 1993, 665-685, (1993).
    • (1993) IEEE Trans, on Syst., Man, Cybernetics , vol.23-3 , pp. 665-685
    • Jang, R.1
  • 15
    • 0030576819 scopus 로고    scopus 로고
    • Learning fuzzy rules and approximate reasoning in fuzzy neural networks and hybrid systems
    • N. Kasabov, "Learning fuzzy rules and approximate reasoning in fuzzy neural networks and hybrid systems, " Fuzzy Sets and Systems 82-2, 2-20, (1996).
    • (1996) Fuzzy Sets and Systems , vol.82-2 , pp. 2-20
    • Kasabov, N.1
  • 16
    • 0031253132 scopus 로고    scopus 로고
    • FuNN/2- A Fuzzy Neural Network Architecture for Adaptive Learning and Knowledge Acquisition
    • J, and
    • N. Kasabov, J, S. Kim, M. Watts and A. Gray, " FuNN/2- A Fuzzy Neural Network Architecture for Adaptive Learning and Knowledge Acquisition, " Information Sciences - Applications, 101(3-4), 155-175, (1997).
    • (1997) Information Sciences - Applications , vol.101 , Issue.3-4 , pp. 155-175
    • Kasabov, N.1    Kim, S.2    Watts, M.3    Gray, A.4
  • 17
    • 85169706321 scopus 로고    scopus 로고
    • The ECOS Framework and the ECO Learning Method for Evolving Connectionist Systems
    • N. Kasabov, "The ECOS Framework and the ECO Learning Method for Evolving Connectionist Systems, " Journal of Advanced Computational Intelligence, 2-6, 195-202, (1998).
    • (1998) Journal of Advanced Computational Intelligence , vol.2-6 , pp. 195-202
    • Kasabov, N.1
  • 18
    • 0002913538 scopus 로고    scopus 로고
    • ECOS: A Framework For Evolving Connectionist Systems And The Eco Learning Paradigm
    • Kitakyushu
    • N. Kasabov, " ECOS: A Framework For Evolving Connectionist Systems And The Eco Learning Paradigm, " Proceedings of ICON IP'98, Kitakyushu, 1232-1237, (1998).
    • (1998) Proceedings of ICON IP'98 , pp. 1232-1237
    • Kasabov, N.1
  • 19
    • 0001961635 scopus 로고    scopus 로고
    • Evolving Fuzzy Neural Networks - Algorithms, Applications and Biological Motivation
    • Iizuka, Japan
    • N. Kasabov, " Evolving Fuzzy Neural Networks - Algorithms, Applications and Biological Motivation, " in Proc. of Iizuka'98, Iizuka, Japan, 217, 274, (1998).
    • (1998) Proc. of Iizuka'98 , vol.217 , pp. 274
    • Kasabov, N.1
  • 20
    • 0010056869 scopus 로고    scopus 로고
    • Evolving Connectionist And Fuzzy Connectionist System For On-Line Decision Making And Control
    • Springer Verlag
    • N. Kasabov, " Evolving Connectionist And Fuzzy Connectionist System For On-Line Decision Making And Control, " in: Soft Computing in Engineering Design and Manufacturing, Springer Verlag, (1999).
    • (1999) Soft Computing in Engineering Design and Manufacturing
    • Kasabov, N.1
  • 21
    • 0141518601 scopus 로고    scopus 로고
    • Evolving Connectionist and Fuzzy-Connect ionist Systems: Theory and Applications for Adaptive, On-line Intelligent Systems
    • N. Kasabov and R. Kozma (eds) Springer Verlag (Physica Verlag)
    • N. Kasabov, "Evolving Connectionist and Fuzzy-Connect ionist Systems: Theory and Applications for Adaptive, On-line Intelligent Systems, " in: N. Kasabov and R. Kozma (eds)" Neuro-fuzzy Tools and Techniques for Intelligent Systems, " Springer Verlag (Physica Verlag), 111-144, (1999).
    • (1999) Neuro-fuzzy Tools and Techniques for Intelligent Systems , pp. 111-144
    • Kasabov, N.1
  • 23
    • 85168771985 scopus 로고    scopus 로고
    • Rule extraction, rule insertion, and reasoning in Evolving Fuzzy Neural Networks
    • N. Kasabov, " Rule extraction, rule insertion, and reasoning in Evolving Fuzzy Neural Networks, " Submitted to Neurocomputing, (1999).
    • (1999) Submitted to Neurocomputing
    • Kasabov, N.1
  • 24
    • 33746161339 scopus 로고
    • Edge Detection Using a Fuzzy Neural Network
    • SP1E, Orlando, Florida
    • D.A, Kerr and J.C. Bczdeck, " Edge Detection Using a Fuzzy Neural Network, " Science of Artificial neural Networks, SP1E, Orlando, Florida, 1710, 510-521, (1992).
    • (1992) Science of Artificial neural Networks , vol.1710 , pp. 510-521
    • Kerr, D.A1    Bczdeck, J.C.2
  • 25
    • 0025489075 scopus 로고
    • The Self-Organizing Map
    • T. Kohoncn, "The Self-Organizing Map, " Proceedings of the IEEE, 78-9, [464-1497, (1990).
    • (1990) Proceedings of the IEEE , vol.78-9 , pp. 464-1497
    • Kohoncn, T.1
  • 26
    • 0003410791 scopus 로고    scopus 로고
    • second edition. Springer Verlag, Berlin
    • T. Kohoncn, "Self-Organizing Maps, " second edition. Springer Verlag, Berlin, (1997).
    • (1997) Self-Organizing Maps
    • Kohoncn, T.1
  • 31
    • 0000864293 scopus 로고    scopus 로고
    • A simple but powerful heuristic method for generating fuzzy rules from numerical data
    • K. Nozaki, H. lsibuchi and H, Tanaka, "A simple but powerful heuristic method for generating fuzzy rules from numerical data, " Fuzzy Sets and Systems, 86, 251-270, (1997).
    • (1997) Fuzzy Sets and Systems , vol.86 , pp. 251-270
    • Nozaki, K.1    lsibuchi, H.2    Tanaka, H3
  • 32
    • 0026927426 scopus 로고
    • Multilayer Pcrceptron, Fuzzy Sets, and Classification
    • S. K. Pal and S. Mitra, "Multilayer Pcrceptron, Fuzzy Sets, and Classification, " IEEE Transactions on Neural Networks, 3-5, 683-697. (1992).
    • (1992) IEEE Transactions on Neural Networks , vol.3-5 , pp. 683-697
    • Pal, S. K.1    Mitra, S.2
  • 33
    • 0028262032 scopus 로고
    • Computational Concepts in Classification: Neural Networks, Statistical Pattern Recognition, and Model-Based Vision
    • L.I. Perlovsky, "Computational Concepts in Classification: Neural Networks, Statistical Pattern Recognition, and Model-Based Vision, " Journal of Mathematical Imaging and Vision, 4-1, 81-110, (1994).
    • (1994) Journal of Mathematical Imaging and Vision , vol.4-1 , pp. 81-110
    • Perlovsky, L.I.1
  • 34
    • 0031016912 scopus 로고    scopus 로고
    • Neuro Fuzzy Approach to Pattern Recognition
    • K.S. Ray and J. Ghoshal, "Neuro Fuzzy Approach to Pattern Recognition, " Neural Networks, 10-1, 161-182, (1997).
    • (1997) Neural Networks , vol.10-1 , pp. 161-182
    • Ray, K.S.1    Ghoshal, J.2
  • 35
    • 38249005526 scopus 로고
    • Fuzzy implication and generalized fuzzy method of cases
    • D. Ruan and E.E. Kcrre, " Fuzzy implication and generalized fuzzy method of cases, " Fuzzy Sets and Systems, 54, 23-37, (1993).
    • (1993) Fuzzy Sets and Systems , vol.54 , pp. 23-37
    • Ruan, D.1    Kcrre, E.E.2
  • 36
    • 0030675044 scopus 로고    scopus 로고
    • Principal Component based BDNN for Face Recognition
    • -97), 1368-1372, (1997).
    • (1997) -97) , pp. 1368-1372
    • Shen, L.1    Fu, H.2
  • 40
    • 0002489083 scopus 로고
    • On the Connection Between In-Sample Testing and Generalization Error
    • D.H. Wolpcrt, "On the Connection Between In-Sample Testing and Generalization Error, " Complex Systems, 6, 47-94, (1992).
    • (1992) Complex Systems , vol.6 , pp. 47-94
    • Wolpcrt, D.H.1


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.